Characteristics of Design and Analysis of Ophthalmic Randomized Controlled Trials: A Review of Ophthalmic Papers 2020-2021

• Published in: Ophthalmology science (Online) Vol. 3; no. 2; p. 100266
• Main Authors: Dong, Ruiqi, Ying, Gui-Shuang
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier 01.06.2023
• Subjects: Original; Ophthalmic Clinical Trials; RCT, randomized clinical trial; Trial Design; Correlated Eye Data; Statistical Analysis; GEE, generalized estimating equations
• ISSN: 2666-9145; 2666-9145
• DOI: 10.1016/j.xops.2022.100266

To evaluate the recent practice of design and statistical analysis of ophthalmic randomized clinical trials (RCTs). Review of 96 ophthalmic RCTs. Two authors (R.D., G.S.Y.) reviewed primary result papers published from January 2020 through December 2021 in , , , and . Data were extracted and analyzed for the characteristics of design (1-eye design, 2-eye design, paired-eye design, and subject design), sample size and power, and statistical analysis for intereye correlation adjustment, missing data, and correction for multiplicity. Characteristics of trial design and statistical analysis. Among 96 RCTs, 50 (52%) used 1-eye design, 21 (22%) 2-eye design, 10 (10%) paired-eye design, and 15 (16%) subject design. In 31 trials of 2-eye design or paired-eye design, 18 (58%) trials had suboptimal analysis of data from both eyes by analyzing data from 1 eye (n = 10), taking the average of 2 eyes (n = 2), analyzing 2 eyes separately (n = 1), ignoring intereye correlation (n = 3), or not specifying how 2-eye data were analyzed (n = 2), and 13 trials (42%) properly adjusted the intereye correlation by using the mixed-effects model (n = 6), paired test (n = 5), generalized estimating equations (n = 1), or marginal Cox regression model (n = 1). Among 96 trials, 75 (78%) provided both sample size and statistical power estimation, and 16 (17%) trials described statistical test for sample size or power estimation. Missing data in primary outcome occurred in 86 (90%) trials with a median missing data rate of 8%, 32 (37%) trials applied statistical methods for missing data, including last value carried forward (n = 10), multiple imputation (n = 14), or other approaches (n = 8). Among 25 trials with > 2 arms, 16 (64%) corrected for multiplicity using the Bonferroni procedure (n = 8), Hochberg procedure (n = 2), Gatekeeping procedure (n = 2), or hierarchical procedure (n = 4). Among 16 trials with multiple primary outcomes, 4 (25%) corrected for multiplicity by the Bonferroni procedure. There are opportunities for improvement in the design and statistical analyses of ophthalmic trials, particularly in the aspects of adjustment for intereye correlation, missing data, and multiplicity. Continuing education in ophthalmology and vision research community may improve the quality of ophthalmic trials. Proprietary or commercial disclosure may be found after the references.